Clustering of gene expression is a useful exploratory technique for gene expression dataset as it groups similar objects together and identify potentially meaningful relationships between the objects. However, there are several issues arise for instance data intensive and redundancy in the cluster. Therefore, the new computational framework is needed in order to handle these issues. The results showed that the proposed computational framework achieved better results compared with other methods. © 2010 Springer-Verlag.
CITATION STYLE
Kasim, S., Deris, S., & Othman, R. M. (2010). A new computational framework for gene expression clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6440 LNAI, pp. 603–610). https://doi.org/10.1007/978-3-642-17316-5_58
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